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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/13625

Title: Delay-Dependent Approach to Robust Stability for Uncertain Discrete Stochastic Recurrent Neural Networks with Interval Time-Varying Delays
Authors: Lu, Chien-Yu;Zheng, Kai-Yuan;Liao, Chin-Wen
Contributors: 工業教育與技術學系
Keywords: Discrete stochastic recurrent neural network;Interval time-varying delay;Linear matrix inequality;Uncertainty;Robust stability
Date: 2008-11
Issue Date: 2012-08-27T10:36:04Z
Publisher: National Cheng Kung University
Abstract: This paper considers the problem of global robust delay-range-dependent stability for uncertain discrete stochastic recurrent neural networks with interval time-varying delays. The parameter uncertainties are assumed to be time-varying norm-bounded in the state equation. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate Lyapunov- Krasovskii functional, global robust delay-dependent stability criterion which is dependent on both the lower bound and upper bound of the interval time-varying delays is derived. A sufficient condition for the discrete stochastic recurrent neural networks with interval time-varying delays is presented in terms of the linear matrix inequality (LMI). An example is given to demonstrate the reduced conservatism of the proposed results in this paper.
Relation: 2008 CACS International Automatic Control Conference, National Cheng Kung University, Tainan, Taiwan, Nov. 21-23, 2008
Appears in Collections:[工業教育與技術學系] 會議論文

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